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Adaptive Equivalent Fuel Consumption Minimization Based Energy Management Strategy for Extended-Range Electric Vehicle

Dongwei YaoCollege of Energy Engineering, Zhejiang University, Hangzhou 310027, ChinaXinwei LuCollege of Energy Engineering, Zhejiang University, Hangzhou 310027, ChinaXiangyun ChaoCollege of Energy Engineering, Zhejiang University, Hangzhou 310027, ChinaYongguang ZhangJunhao ShenCollege of Energy Engineering, Zhejiang University, Hangzhou 310027, ChinaFanlong ZengCollege of Energy Engineering, Zhejiang University, Hangzhou 310027, ChinaZiyan ZhangCollege of Energy Engineering, Zhejiang University, Hangzhou 310027, ChinaFeng WuCollege of Energy Engineering, Zhejiang University, Hangzhou 310027, China
2023en
ABI

Annotatsiya

Unlike battery electric vehicles, extended-range electric vehicles have one more energy source, so a reasonable energy management strategy (EMS) is crucial to the fuel economy of the vehicles. In this paper, an adaptive equivalent fuel consumption minimization strategy (A-ECMS)-based energy management strategy is proposed for the extended-range electric vehicle. The equivalent fuel consumption minimization strategy (ECMS), which utilizes Pontryagin’s minimum principle (PMP), is introduced to design the EMS. Compared with other ECMS strategies, an adaptive equivalent factor algorithm, based on state of charge (SOC) feedback and a proportional–integral (PI) controller is designed to update the equivalent factor under different working conditions. Additionally, a start–stop penalty is added to the objective function to take the dynamic start–stop process of the range extender into account. As a result, under the WLTC driving cycle, the proposed strategy can achieve 6.78 L/100 km comprehensive fuel consumption, saving 6.2% and 3.4% fuel consumption compared with the conventional rule-based thermostat strategy and the power following strategy. Moreover, the proposed EMS achieves the lowest ampere-hour flux among the three EMSs, indicating its ability to improve battery life.

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